Hy-Nomas Ships 8B Interactive World Model on a Single RTX 4090

Hy-Nomas, an 8B diffusion video world model, generates a 100-second clip at 1280×704 and 24 FPS on a single RTX 4090, with peak GPU memory of 20.53 GiB.

The release, posted on Hugging Face, pairs that inference recipe with pairwise human-evaluation numbers against three baselines. On the multi-turn free-form text benchmark, Hy-Nomas beats LingBot-World v2 75.0% of the time on prompt following and 68.3% on physical plausibility. On the interleaved text-and-camera benchmark, the numbers against the adapted LingBot-World v2 are 75.0%, 73.3%, and 26.7% across prompt following, physical plausibility, and camera control respectively.

Against Google DeepMind's Genie 3 the picture flips. On spatial memory, which tests object permanence after a viewpoint revisit, Hy-Nomas wins 13.3% of comparisons, ties 56.7%, and loses 30.0%. The paper names this as an area for improvement.

The abstract's core design claim: "Our central design aligns structured video captions with action-aware causal attention: descriptive context remains accessible across segments, while action instructions are restricted to their intended temporal windows." The 8B backbone is a 54-block MMDiT paired with a Qwen2.5-VL-7B text encoder, and Hy-Nomas-Bench bundles 280 test cases across four benchmarks, hosted at huggingface.co/datasets/tencent/Hy-Nomas-Bench.

The 4090 recipe is not trivial: INT8 quantization, sliding-window attention, and CPU offloading sit behind the 20.53 GiB figure. Weights, training code, and a LoRA adaptation workflow ship together, and the paper demonstrates cinematic and robotics LoRAs trained on roughly 100 and 128 clips respectively. Google DeepMind debuted Genie 4 the day before.